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Database Design Theory CS405G: Introduction to Database Systems

Database Design Theory CS405G: Introduction to Database Systems. Jinze Liu. Normalization. Normalization We discuss four normal forms: first, second, third, and Boyce- Codd normal forms 1NF, 2NF, 3NF, and BCNF

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Database Design Theory CS405G: Introduction to Database Systems

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  1. Database Design Theory CS405G: Introduction to Database Systems Jinze Liu

  2. Normalization • Normalization • We discuss four normal forms: first, second, third, and Boyce-Codd normal forms • 1NF, 2NF, 3NF, and BCNF • Normalization is a process that “improves” a database design by generating relations that are of higher normal forms. • The objective of normalization: • “to create relations where every dependency is on the key, the whole key, and nothing but the key”.

  3. Normalization • There is a sequence to normal forms: • 1NF is considered the weakest, • 2NF is stronger than 1NF, • 3NF is stronger than 2NF, and • BCNF is considered the strongest • Also, • any relation that is in BCNF, is in 3NF; • any relation in 3NF is in 2NF; and • any relation in 2NF is in 1NF.

  4. Normalization 1NF a relation in BCNF, is also in 3NF a relation in 3NF is also in 2NF a relation in 2NF is also in 1NF 2NF 3NF BCNF

  5. Normalization • The benefit of higher normal forms is that update semantics for the affected data are simplified. • This means that applications required to maintain the database are simpler. • A design that has a lower normal form than another design has more redundancy. Uncontrolled redundancy can lead to data integrity problems. • First we introduce the concept of functional dependency

  6. Review • Functional dependencies • X->Y: X “determines” Y • If two rows agree on X, they must agree on Y • A generalization of the key concepts y1

  7. Functional Dependencies EmpNum EmpEmail EmpNum EmpFname EmpNum EmpLname 3 different ways you might see FDs depicted EmpEmail EmpNum EmpEmail EmpEmail EmpNum EmpEmail EmpFname EmpLname

  8. Determinant Functional Dependency EmpNum EmpEmail • Attribute on the LHS is known as the determinant • EmpNum is a determinant of EmpEmail

  9. ssn pnumber hours ename plocation What functional dependencies? EmployeeProject WORKS ON Essn pno hours

  10. Transitive dependency Transitive dependency Consider attributes A, B, and C, and where A  B and B  C. Functional dependencies are transitive, which means that we also have the functional dependency A  C We say that C is transitively dependent on A through B.

  11. Transitive dependency EmpNum  DeptNum EmpNumEmpEmail DeptNum DeptNname DeptNum  DeptName EmpNumEmpEmail DeptNum DeptNname • DeptName is transitively dependent on EmpNum via DeptNum • EmpNum  DeptName

  12. Partial dependency A partial dependency exists when an attribute B is functionally dependent on an attribute A, and A is a component of a multipart candidate key. InvNum LineNum Qty InvDate Candidate keys: {InvNum, LineNum} InvDate is partially dependent on {InvNum, LineNum} as InvNum is a determinant of InvDate and InvNum is part of a candidate key

  13. First Normal Form First Normal Form We say a relation is in 1NF if all values stored in the relation are single-valued and atomic. 1NF places restrictions on the structure of relations. Values must be simple.

  14. First Normal Form The following is not in 1NF EmpNum EmpPhone EmpDegrees 123 233-9876 333 233-1231 BA, BSc, PhD 679 233-1231 BSc, MSc • EmpDegrees is a multi-valued field: • employee 679 has two degrees: BSc and MSc • employee 333 has three degrees: BA, BSc, PhD

  15. EmpNum EmpPhone EmpDegrees 123 233-9876 333 233-1231 BA, BSc, PhD 679 233-1231 BSc, MSc First Normal Form To obtain 1NF relations we must, without loss of information, replace the above with two relations - see next slide What would the ERD be for the above situation with EmpNum, EmpPhone, EmpDegrees. Would we have generated the above table using our “mapping algorithm”?

  16. First Normal Form EmployeeDegree Employee EmpNum EmpDegree EmpNum EmpPhone 333 BA 123 233-9876 333 BSc 333 233-1231 333 PhD 679 233-1231 679 BSc 679 MSc An outer join between Employee and EmployeeDegree will produce the information we saw before

  17. Boyce-Codd Normal Form InvNum LineNum ProdNum Qty InvNum, LineNum ProdNum {InvNum, LineNum} and {InvNum, ProdNum} are the two candidate keys. Qty InvNum, ProdNum LineNum There are two candidate keys. Since every determinant is a candidate key, the relation is in BCNF This relation is about Invoice lines only.

  18. Second Normal Form • Second Normal Form • A relation is in 2NF if it is in 1NF, and every non-key attribute is fully dependent on each candidate key. (That is, we don’t have any partial functional dependency.) • 2NF (and 3NF) both involve the concepts of key and non-key attributes. • A key attribute is any attribute that is part of a key; any attribute that is not a key attribute, is a non-key attribute. • Relations that are not in BCNF have data redundancies • A relation in 2NF will not have any partial dependencies

  19. Second Normal Form Consider this InvLine table (in 1NF): InvNum LineNum ProdNum Qty InvDate InvNum, LineNum ProdNum There are two candidate keys. Qty InvNum, ProdNum LineNum Qty is the only non-key attribute, and it is dependent on InvNum InvNum InvDate Since there is a determinant that is not a candidate key, InvLine is not BCNF InvLine is not 2NF since there is a partial dependency of InvDate on InvNum InvLine is only in 1NF

  20. Second Normal Form InvLine InvNum LineNum ProdNum Qty InvDate The above relation has redundancies: the invoice date is repeated on each invoice line. We can improve the database by decomposing the relation into two relations: InvNum LineNum ProdNum Qty InvNum InvDate Question: What is the highest normal form for these relations? 2NF? 3NF? BCNF?

  21. inv_no line_no prod_no prod_desc qty 2NF, but not in 3NF, nor in BCNF: since prod_no is not a candidate key and we have: prod_no  prod_desc.

  22. EmployeeDept ename ssn bdate address dnumber dname 2NF, but not in 3NF, nor in BCNF: since dnumber is not a candidate key and we have: dnumber  dname.

  23. Third Normal Form Third Normal Form a relation is in 3NF if the relation is in 1NF and all determinants of non-key attributes are candidate keys That is, for any functional dependency: X  Y, where Y is a non-key attribute (or a set of non-key attributes), X is a candidate key. this definition of 3NF differs from BCNF only in the specification of non-key attributes - 3NF is weaker than BCNF. (BCNF requires all determinants to be candidate keys.) A relation in 3NF will not have any transitive dependencies

  24. Boyce-Codd Normal Form • Boyce-Codd Normal Form • BCNF is defined very simply: • a relation is in BCNF if it is in 1NF and if every determinant is a candidate key. If our database will be used for OLTP (on line transaction processing), then BCNF is our target. Usually, we meet this objective. However, we might denormalize (3NF, 2NF, or 1NF) for performance reasons.

  25. Third Normal Form Consider this Employee relation Candidate keys are? … EmpNum EmpName DeptNum DeptName EmpName, DeptNum, and DeptName are non-key attributes. DeptNum determines DeptName, a non-key attribute, and DeptNum is not a candidate key. Is the relation in 3NF? … no Is the relation in 2NF? … yes Is the relation in BCNF? … no

  26. EmpNum EmpName DeptNum DeptName We correct the situation by decomposing the original relation into two 3NF relations. Note the decomposition is lossless. DeptNum DeptName EmpNum EmpName DeptNum Third Normal Form Verify these two relations are in 3NF. Are they in BCNF?

  27. In 3NF, but not in BCNF: Instructor teaches one course only. student_no course_no instr_no Student takes a course and has one instructor. {student_no, course_no}  instr_no instr_no  course_no since we have instr_no  course-no, but instr_no is not a Candidate key.

  28. student_no course_no instr_no BCNF student_no instr_no course_no instr_no {student_no, instr_no}  student_no {student_no, instr_no}  instr_no instr_no  course_no

  29. Another example: 3NF • Address (street_address, city, state, zip) • street_address, city, state->zip • zip->city, state • Keys • {street_address, city, state} • {street_address, zip} • BCNF? • Violation: zip->city, state

  30. To decompose or not to decompose Address1 (zip, city, state) Address2 (street_address, zip) • FD’s in Address1 • zip->city, state • FD’s in Address2 • None! • Hey, where is street_address, city, state->zip? • Cannot check without joining Address1 and Address2 back together • Dilemma: Should we get rid of redundancy at the expense of making constraints harder to enforce?

  31. BCNF = no redundancy? • Student (SID, CID, club) • Suppose your classes have nothing to do with the clubs you join • FD’s? • None • BCNF? • Yes • Redundancies? • Tons!

  32. Multivalued dependencies • A multivalued dependency (MVD) has the formX->>Y, where X and Y are sets of attributes in a relation R • X ->>Y means that whenever two rows in R agree on all the attributes of X, then we can swap their Y components and get two new rows that are also in R Must be in R too

  33. 4NF violation: SID ->>CID Enroll (SID, CID) Join (SID, club) 4NF 4NF 4NF decomposition example Student (SID, CID, club)

  34. 3NF, BCNF, 4NF, and beyond • Of historical interests • 1NF: All column values must be atomic • 2NF: Slightly more relaxed than 3NF

  35. Summary • Philosophy behind BCNF, 4NF:Data should depend on the key, the whole key, and nothing but the key! • Philosophy behind 3NF: … But not at the expense of more expensive constraint enforcement!

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